code: def cutout_bbox(
      image: tf.Tensor,
      rng: int,
      denoise_configs: ml_collections.ConfigDict,
      dtype: tf.DType = tf.float32,
  ) -> Tuple[tf.Tensor, tf.Tensor]:
      """Cuts out portions of the given image by sampling random bounding boxes.
  
      Args:
        image: A single image, must be in 0-1 range.
        rng: Seed for sampling the noise.
        denoise_configs: Configurations for the denoising process.
        dtype: Data type of the image.
  
      Returns:
        The corrupted image and the noise.
      """
      del rng
  
      noise = get_mask(image, denoise_configs, dtype)
      noised_image = image * (1 - noise) + 0.5 * noise
      return noised_image, noise
  
file_path: scenic/scenic/projects/robust_segvit/datasets/denoise_utils.py
imports: from typing import Tuple, Optional
  from absl import logging
  import ml_collections
  import tensorflow
label_desc: Use image node_id 2 for calling a global function with example usage: cutout_bbox(image, rng, denoise_configs, dtype) and returns: noised_image,  noise